R: Statistical Inference in Partial Linear Regression Models

# Statistical Inference in Partial Linear Regression Models

## Documentation for package ‘PLRModels’ version 1.4

- DESCRIPTION file

## Help Pages

PLRModels-package | Statistical inference in partial linear regression models
barnacles1 | Sales of barnacles in Cedeira
barnacles2 | Sales of barnacles in Cangas
np.ancova | Nonparametric analysis of covariance
np.cv | Cross-validation bandwidth selection in nonparametric regression models
np.est | Nonparametric estimate of the regression function
np.gcv | Generalized cross-validation bandwidth selection in nonparametric regression models
np.gof | Goodness-of-Fit tests in nonparametric regression models
par.ancova | Parametric analysis of covariance (based on linear models)
par.ci | Confidence intervals estimation in linear regression models
par.est | Estimation in linear regression models
par.gof | Goodness-of-Fit tests in linear regression models
plrm.ancova | Semiparametric analysis of covariance (based on PLR models)
plrm.beta | Semiparametric estimate for the parametric component of the regression function in PLR models
plrm.ci | Confidence intervals estimation in partial linear regression models
plrm.cv | Cross-validation bandwidth selection in PLR models
plrm.est | Semiparametric estimates for the unknown components of the regression function in PLR models
plrm.gcv | Generalized cross-validation bandwidth selection in PLR models
plrm.gof | Goodness-of-Fit tests in PLR models
PLRModels | Statistical inference in partial linear regression models